GazeNet: A lightweight multitask sclera feature extractor
The sclera is a recently emergent biometric modality with many desirable characteristics. However, most literature solutions for sclera-based recognition rely on sequences of complex deep networks with significant computational overhead. In this paper, we propose a lightweight multitask-based sclera...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Alexandria Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016824014273 |
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| _version_ | 1832583091810467840 |
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| author | Matej Vitek Vitomir Štruc Peter Peer |
| author_facet | Matej Vitek Vitomir Štruc Peter Peer |
| author_sort | Matej Vitek |
| collection | DOAJ |
| description | The sclera is a recently emergent biometric modality with many desirable characteristics. However, most literature solutions for sclera-based recognition rely on sequences of complex deep networks with significant computational overhead. In this paper, we propose a lightweight multitask-based sclera feature extractor. The proposed GazeNet network has a computational complexity below 1 GFLOP, making it appropriate for less capable devices like smartphones and head-mounted displays. Our experiments show that GazeNet (which is based on the SqueezeNet architecture) outperforms both the base SqueezeNet model as well as the more computationally intensive ScleraNET model from the literature. Thus, we demonstrate that our proposed gaze-direction multitask learning procedure, along with careful lightweight architecture selection, leads to computationally efficient networks with high recognition performance. |
| format | Article |
| id | doaj-art-62aa6c7e56d44f8ebf433cc6f41aef96 |
| institution | Kabale University |
| issn | 1110-0168 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj-art-62aa6c7e56d44f8ebf433cc6f41aef962025-01-29T05:00:18ZengElsevierAlexandria Engineering Journal1110-01682025-01-01112661671GazeNet: A lightweight multitask sclera feature extractorMatej Vitek0Vitomir Štruc1Peter Peer2Corresponding author.; University of Ljubljana, Ljubljana, SloveniaUniversity of Ljubljana, Ljubljana, SloveniaUniversity of Ljubljana, Ljubljana, SloveniaThe sclera is a recently emergent biometric modality with many desirable characteristics. However, most literature solutions for sclera-based recognition rely on sequences of complex deep networks with significant computational overhead. In this paper, we propose a lightweight multitask-based sclera feature extractor. The proposed GazeNet network has a computational complexity below 1 GFLOP, making it appropriate for less capable devices like smartphones and head-mounted displays. Our experiments show that GazeNet (which is based on the SqueezeNet architecture) outperforms both the base SqueezeNet model as well as the more computationally intensive ScleraNET model from the literature. Thus, we demonstrate that our proposed gaze-direction multitask learning procedure, along with careful lightweight architecture selection, leads to computationally efficient networks with high recognition performance.http://www.sciencedirect.com/science/article/pii/S1110016824014273BiometricsOcular biometricsSclera recognitionLightweightFeature extraction |
| spellingShingle | Matej Vitek Vitomir Štruc Peter Peer GazeNet: A lightweight multitask sclera feature extractor Alexandria Engineering Journal Biometrics Ocular biometrics Sclera recognition Lightweight Feature extraction |
| title | GazeNet: A lightweight multitask sclera feature extractor |
| title_full | GazeNet: A lightweight multitask sclera feature extractor |
| title_fullStr | GazeNet: A lightweight multitask sclera feature extractor |
| title_full_unstemmed | GazeNet: A lightweight multitask sclera feature extractor |
| title_short | GazeNet: A lightweight multitask sclera feature extractor |
| title_sort | gazenet a lightweight multitask sclera feature extractor |
| topic | Biometrics Ocular biometrics Sclera recognition Lightweight Feature extraction |
| url | http://www.sciencedirect.com/science/article/pii/S1110016824014273 |
| work_keys_str_mv | AT matejvitek gazenetalightweightmultitasksclerafeatureextractor AT vitomirstruc gazenetalightweightmultitasksclerafeatureextractor AT peterpeer gazenetalightweightmultitasksclerafeatureextractor |